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Open AccessArticle

Establishing Raw Acceleration Thresholds to Classify Sedentary and Stationary Behaviour in Children

Physical Activity Exchange, Department of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 2EX, UK
Department of Sport and Physical Activity, Edge Hill University, Ormskirk L39 4QP, UK
Public Health Institute, Faculty of Education, Health and Community, Liverpool John Moores University, Liverpool L2 2QP, UK
School of Health and Society, Salford University, Manchester M6 6PU, UK
Author to whom correspondence should be addressed.
Children 2018, 5(12), 172;
Received: 31 October 2018 / Revised: 12 December 2018 / Accepted: 17 December 2018 / Published: 19 December 2018
(This article belongs to the Special Issue Physical Activity and Sedentary Behaviour in Children and Adolescents)
This study aimed to: (1) compare acceleration output between ActiGraph (AG) hip and wrist monitors and GENEActiv (GA) wrist monitors; (2) identify raw acceleration sedentary and stationary thresholds for the two brands and placements; and (3) validate the thresholds during a free-living period. Twenty-seven from 9- to 10-year-old children wore AG accelerometers on the right hip, dominant- and non-dominant wrists, GA accelerometers on both wrists, and an activPAL on the thigh, while completing seven sedentary and light-intensity physical activities, followed by 10 minutes of school recess. In a subsequent study, 21 children wore AG and GA wrist monitors and activPAL for two days of free-living. The main effects of activity and brand and a significant activity × brand × placement interaction were observed (all p < 0.0001). Output from the AG hip was lower than the AG wrist monitors (both p < 0.0001). Receiver operating characteristic (ROC) curves established AG sedentary thresholds of 32.6 mg for the hip, 55.6 mg and 48.1 mg for dominant and non-dominant wrists respectively. GA wrist thresholds were 56.5 mg (dominant) and 51.6 mg (non-dominant). Similar thresholds were observed for stationary behaviours. The AG non-dominant threshold came closest to achieving equivalency with activPAL during free-living. View Full-Text
Keywords: accelerometers; wearable technology; activity classification; cut points accelerometers; wearable technology; activity classification; cut points
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Hurter, L.; Fairclough, S.J.; Knowles, Z.R.; Porcellato, L.A.; Cooper-Ryan, A.M.; Boddy, L.M. Establishing Raw Acceleration Thresholds to Classify Sedentary and Stationary Behaviour in Children. Children 2018, 5, 172.

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