Literature DB >> 31518999

Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children.

Kimberly A Clevenger1, Karin A Pfeiffer, Kelly A Mackintosh, Melitta A McNarry, Jan Brønd, Daniel Arvidsson, Alexander H K Montoye.   

Abstract

Sampling rate (Hz) of ActiGraph accelerometers may affect processing of acceleration to activity counts when using a hip-worn monitor, but research is needed to quantify if sampling rate affects actual acceleration (mgs), when using wrist-worn accelerometers and during non-locomotive activities.
OBJECTIVE: To assess the effect of ActiGraph sampling rate on total counts/15 s and mean acceleration and to compare differences due to sampling rate between accelerometer wear locations and across different types of activities. APPROACH: Children (n  =  29) wore a hip- and wrist-worn accelerometer (sampled at 100 Hz, downsampled in MATLAB to 30 Hz) during rest/transition periods, active video games, and a treadmill test to volitional exhaustion. Mean acceleration and counts/15 s were computed for each axis and as vector magnitude. MAIN
RESULTS: There were mostly no significant differences in mean acceleration. However, 100 Hz data resulted in significantly more total counts/15 s (mean bias 4-43 counts/15 s across axes) for both the hip- and wrist-worn monitor when compared to 30 Hz data. Absolute differences increased with activity intensity (hip: r  =  0.46-0.63; wrist: r  =  0.26-0.55) and were greater for hip- versus wrist-worn monitors. Percent agreement between 100 and 30 Hz data was high (97.4%-99.7%) when cut-points or machine learning algorithms were used to classify activity intensity. SIGNIFICANCE: Our findings support that sampling rate affects the generation of counts but adds that differences increase with intensity and when using hip-worn monitors. We recommend researchers be consistent and vigilantly report the sampling rate used, but note that classifying data into activity intensities resulted in agreement despite differences in sampling rate.

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Year:  2019        PMID: 31518999     DOI: 10.1088/1361-6579/ab444b

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  7 in total

1.  Homes became the "everything space" during COVID-19: impact of changes to the home environment on children's physical activity and sitting.

Authors:  Michael P R Sheldrick; Nils J Swindell; Amie B Richards; Stuart J Fairclough; Gareth Stratton
Journal:  Int J Behav Nutr Phys Act       Date:  2022-10-21       Impact factor: 8.915

2.  Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.

Authors:  Alex V Rowlands; Nathan P Dawkins; Ben Maylor; Charlotte L Edwardson; Stuart J Fairclough; Melanie J Davies; Deirdre M Harrington; Kamlesh Khunti; Tom Yates
Journal:  Sports Med Open       Date:  2019-12-05

3.  Identifying bedrest using waist-worn triaxial accelerometers in preschool children.

Authors:  J Dustin Tracy; Thomas Donnelly; Evan C Sommer; William J Heerman; Shari L Barkin; Maciej S Buchowski
Journal:  PLoS One       Date:  2021-01-28       Impact factor: 3.240

4.  The Cut-Off Value for Classifying Active Italian Children Using the Corresponding National Version of the Physical Activity Questionnaire.

Authors:  Corrado Lupo; Gennaro Boccia; Alexandru Nicolae Ungureanu; Anna Mulasso; Paolo De Pasquale; Annamaria Mancini; Pasqualina Buono; Alberto Rainoldi; Paolo Riccardo Brustio
Journal:  Sports (Basel)       Date:  2022-04-14

5.  Investigating Wrist-Based Acceleration Summary Measures across Different Sample Rates towards 24-Hour Physical Activity and Sleep Profile Assessment.

Authors:  Athanasios Tsanas
Journal:  Sensors (Basel)       Date:  2022-08-17       Impact factor: 3.847

6.  Associations between the Home Physical Environment and Children's Home-Based Physical Activity and Sitting.

Authors:  Michael P Sheldrick; Clover Maitland; Kelly A Mackintosh; Michael Rosenberg; Lucy J Griffiths; Richard Fry; Gareth Stratton
Journal:  Int J Environ Res Public Health       Date:  2019-10-29       Impact factor: 3.390

7.  The Gender Difference in Association between Home-Based Environment and Different Physical Behaviors of Chinese Adolescents.

Authors:  Xiao Hou; Jing-Min Liu; Zheng-Yan Tang; Bing Ruan; Xu-Yao Cao
Journal:  Int J Environ Res Public Health       Date:  2020-11-03       Impact factor: 3.390

  7 in total

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