KIT | KIT-Bibliothek | Impressum | Datenschutz

Processing accelerometer data of children and adolescents - influence of wear time algorithm, epoch length and cut-off points on age specific subgroups

Anedda, Bastian; Niessner, Claudia; Burchartz, Alexander; Oriwol, Doris; Schmidt, Steffen; Woll, Alexander

Abstract (englisch):
INTRODUCTION: In order to determine physical activity (PA) in free-living conditions the most common used objective method is accelerometry. Large-scale epidemiologic studies frequently use “counts” derived from the ActiGraph device to classify PA. The PA outcome is influenced by different parameters set during data collection and data processing. The aim of this study was to analyse the effect of epoch length (EL), wear time (WT) algorithm and cut-off points (CP) on PA outcome for age specific subgroups within the sample of the Motorik-Modul-Study (MoMo) (Woll et al., 2017).
METHODS: 1,848 children and adolescents between the age of 6 and 17 (N(male) = 901, N(female)=947) wore either ActiGraph GT3x+ or ActiGraph wGT3X-BT as part of the examination throughout the nationwide MoMo survey “Wave 2” (2014-2017). The participants wore the device during all waking hours on 8 consecutive days. The device was placed laterally at the hip and data was sampled with a frequency of 30Hz. Afterwards data was downloaded and converted into one second epochs using ActiLife. Further data processing was done in MATLAB. Data was reintegrated into 5, 15 and 60 second epochs and Troiano (Troiano et al., 2008) and Choi (Choi et al., 2011) WT algorithms were applied. ... mehr



Zugehörige Institution(en) am KIT Institut für Sport und Sportwissenschaft (IfSS)
Publikationstyp Vortrag
Jahr 2018
Sprache Englisch
Identifikator KITopen-ID: 1000090698
Veranstaltung 23rd Annual Congress of the European College of Sport Science (ECSS 2018), Dublin, Irland, 04.07.2018 – 07.07.2018
Projektinformation MoMo-LS-Studie (BMBF, 01ER1503A)
Schlagworte Accelerometer, Physical Activity, MoMo-Study, Epoch Length, Non-Wear-Time, intensitiy classification algorithms
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page