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The Intrinsic Properties of ActiGraph Counts and Alternatives

Jan Christian Brønd, Niels Christian Møller, and Anders Grøntved

. , Jespersen , E. , Franz , C. , Klakk , H. , Heidemann , M. , Christiansen , C. , Møller , N.C. , & Leboeuf-Yde , C. ( 2012 ). Study protocol. The Childhood Health, Activity, and Motor Performance School Study Denmark (The CHAMPS-study DK) . BMC Pediatrics, 12 , Article 128 . Winther , D

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Integrity and Performance of Four Tape Solutions for Mounting Accelerometry Devices: Lolland-Falster Health Study

Therese Lockenwitz Petersen, Jan C. Brønd, Eva Benfeldt, and Randi Jepsen

Background: Tape-mounted Axivity AX3 accelerometers are increasingly being used to monitor physical activity of individuals, but studies on the integrity and performance of diffe1rent attachment protocols are missing. Purpose: The purpose of this paper was to evaluate four attachment protocols with respect to skin reactions, adhesion, and wear time in children and adults using tape-mounted Axivity AX3 accelerometers and to evaluate the associated ease of handling. Methods: We used data from the Danish household-based population study, the Lolland-Falster Health Study. Participants were instructed to wear accelerometers for seven consecutive days and to complete a questionnaire on skin reactions and issues relating to adhesion. A one-way analysis of variance was used to examine differences in skin reactions and adhesion between the protocols. A Tukey post hoc test compared group means. Ease of handling was assessed throughout the data collection. Results: In total, 5,389 individuals were included (1,289 children and 4,100 adults). For both children and adults, skin reactions were most frequent in Protocols 1 and 2. Adhesion problems were most frequent in Protocol 3. Wear time was longest in Protocol 4. Skin reactions and adhesion problems were more frequent in children compared to adults. Adults achieved longest wear time. Discussion: Covering the skin completely with adhesive tape seemed to cause skin reactions. Too short pieces of fixation tape caused accelerometers to fall off. Protocols necessitating removal of remains of glue on the accelerometers required a lot of work. Conclusion: The last of the four protocols was superior in respect to skin reactions, adhesion, wear time, and ease of handling.

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Prediction Strength for Clustering Activity Patterns Using Accelerometer Data

Jingzhi Yu, Kristopher Kapphahn, Hyatt Moore, Farish Haydel, Thomas Robinson, and Manisha Desai

Background: Clustering, a class of unsupervised machine learning methods, has been applied to physical activity data recorded by accelerometers to discover unique patterns of physical activity and health outcomes. The prediction strength metric provides a criterion to determine the optimal number of clusters for clustering methods. The aim of this study is to provide specific guidance for applying prediction strength to time series accelerometer data. Methods: For this purpose, we designed an extensive simulation study. We created a synthetic data set of accelerometer data using data from a childhood obesity management trial. We evaluated the role of a prespecified threshold of the prediction strength metric as a key input parameter. We compared the recommended threshold (between 0.8 and 0.9) with an approach we developed (Local Maxima). Results: The choice of threshold had a large impact on performance. When the noise level increased (greater overlap between true clusters), lower thresholds outperformed the recommended threshold, which tended to underestimate the true number of clusters. In addition, we found that sorting the data by magnitude of intensity in windows within the time series of interest prior to clustering alleviated sensitivity to threshold choice. Furthermore, for accelerometer data, we recommend that the Local Maxima approach be utilized together with a graphical evaluation of the prediction strength metric function over values of k. Finally, we strongly suggest sorting of the data prior to clustering if sorting retains meaning for the research question at hand. Conclusion: Our recommendations can help future researchers discover more robust patterns from accelerometer data.

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Association of Individual Motor Abilities and Accelerometer-Derived Physical Activity Measures in Preschool-Aged Children

Becky Breau, Berit Brandes, Marvin N. Wright, Christoph Buck, Lori Ann Vallis, and Mirko Brandes

Early childhood (3–5 years of age) presents a critical time for development during which children learn to move through space and acquire fundamental movement skills (FMS) such as running and jumping ( Stodden et al., 2008 ). The development of motor competency is a complex process driven by

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The KID Study (Kids Interacting With Dogs): Piloting a Novel Approach for Measuring Dog-Facilitated Youth Physical Activity

Colleen J. Chase, Sarah Burkart, and Katie Potter

childhood physical activity (PA), including more favorable cardiometabolic health, muscular and cardiorespiratory fitness, bone health, and mental health ( Bailey et al., 2018 ; Carter et al., 2016 ; Centers for Disease Control and Prevention, 2008 ). Additionally, higher childhood PA is linked to higher

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Methodology for Assessing Infant (0–2 Years) Movement Using Accelerometers: A Scoping Review

Danae Dinkel, John P. Rech, Priyanka Chaudhary, Rama Krishna Thelagothoti, Jon Youn, Hesham Ali, Michaela Schenkelberg, and Brian Knarr

Physical activity is widely recognized as a requirement to achieve and maintain optimal health and body weight across the lifespan, beginning in infancy ( Carson et al., 2017 ; Piercy et al., 2018 ). During early childhood, physical activity is essential for overall development. Specifically

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Association Between Accelerometer and Parental Reported Weekend and Weekday Sleeping Patterns and Adiposity Among Preschool-Aged Children

Bridget Coyle-Asbil, Hannah J. Coyle-Asbil, David W.L. Ma, Jess Haines, and Lori Ann Vallis

Early childhood is a critical window during which children are at risk for developing nighttime settling and sleep difficulties that can persist with age ( Lebourgeois, Wright, Lebourgeois, & Jenni, 2013 ). According to the Canadian Society for Exercise and Physiology, as well as the World Health

Open access

Simulation-Based Evaluation of Methods for Handling Nonwear Time in Accelerometer Studies of Physical Activity

Kristopher I. Kapphahn, Jorge A. Banda, K. Farish Haydel, Thomas N. Robinson, and Manisha Desai

-sponsored Childhood Obesity Prevention and Treatment Research Consortium ( Pratt et al., 2013 ; Robinson et al., 2013 ). Preparation of the Accelerometer Data Sampling Pool For simplicity and without loss of generality to other univariable measures such as the triaxial-based vector of magnitude, we generated data

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Validity of a Novel Algorithm to Detect Bedtime, Wake Time, and Sleep Time in Adults

Kyle R. Leister, Jessica Garay, and Tiago V. Barreira

60-s epochs using a low-frequency extension filter to detect low-magnitude accelerations. An ActiGraph sleep algorithm developed for the International Study of Childhood Obesity, Lifestyle, and the Environment and later validated in young adults was used to compute sleep variables including bedtime

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Bidirectional Day-to-Day Associations of Reported Sleep Duration With Accelerometer Measured Physical Activity and Sedentary Time Among Dutch Adolescents: An Observational Study

Nathalie Berninger, Gregory Knell, Kelley Pettee Gabriel, Guy Plasqui, Rik Crutzen, and Gill Ten Hoor

.pdf Chaput , J.-P. , Saunders , T. , & Carson , V. ( 2017 ). Interactions between sleep, movement and other non-movement behaviours in the pathogenesis of childhood obesity . Obesity Reviews, 18, 7 – 14 . PubMed ID: 28164448 doi:10.1111/obr.12508 10.1111/obr.12508 Chastin , S.F. , Palarea