title: Validation of the SenseWear Mini activity monitor in 5-12-year-old children.
abstract: OBJECTIVE
  This study aimed to validate SenseWear Mini software algorithm versions 2.2 (SW2.2) and 5.2 (SW5.2) for estimating energy expenditure (EE) in children.
  
  
  METHODS
  Laboratory-based validation study.
  
  
  METHODS
  57 children aged 5-12 y completed a protocol involving 15 semi-structured sedentary (SED), light-intensity (LPA), and moderate- to vigorous-intensity (MVPA) physical activities. EE was estimated using portable indirect calorimetry (IC). The accuracy of EE estimates (kcal·min-1) from SW2.2 and SW5.2 were examined at the group level and individual level using the mean absolute percentage error (MAPE), Bland-Altman plots and equivalence testing.
  
  
  RESULTS
  MAPE values were lower for SW5.2 (30.1±10.7%) than for SW2.2 (44.0±6.2%). Although mean differences for SW5.2 were smaller than for SW2.2 during SED (-0.23±0.22 vs. -0.61±0.20kcal·min-1), LPA (-0.69±0.76 vs. -1.07±0.46kcal·min-1) and MVPA (-2.22±1.15 vs. -2.57±1.15kcal·min-1), limits of agreement did not decrease for the updated algorithms. For all activities, SW2.2 and SW5.2 were not equivalent to IC (p>0.05). Errors increased with increasing intensity.
  
  
  CONCLUSIONS
  The current SenseWear Mini algorithms SW5.2 underestimated EE. The overall improved accuracy for SW5.2 was not accompanied with improved accuracy at the individual level and EE estimates were not equivalent to IC.
authors.affiliation: Early Start Research Institute, Faculty of Social Sciences, University of Wollongong, Australia. Electronic address: cmtvl646@uowmail.edu.au.
authors.forename: Christiana M T
authors.initials: CM
authors.lastname: van Loo
authors.affiliation: Early Start Research Institute, Faculty of Social Sciences, University of Wollongong, Australia.
authors.forename: Anthony D
authors.initials: AD
authors.lastname: Okely
authors.affiliation: School of Mathematics and Applied Statistics, University of Wollongong, Australia.
authors.forename: Marijka J
authors.initials: MJ
authors.lastname: Batterham
authors.affiliation: Deakin University, Geelong, Australia, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Australia.
authors.forename: Trina
authors.initials: T
authors.lastname: Hinkley
authors.affiliation: Norwegian School of Sports Sciences, Norway; MRC Epidemiology Unit, University of Cambridge, United Kingdom.
authors.forename: Ulf
authors.initials: U
authors.lastname: Ekelund
authors.affiliation: MRC Epidemiology Unit, University of Cambridge, United Kingdom.
authors.forename: Søren
authors.initials: S
authors.lastname: Brage
authors.affiliation: University of Strathclyde, School of Psychological Sciences and Health, Scotland.
authors.forename: John J
authors.initials: JJ
authors.lastname: Reilly
authors.affiliation: School of Medicine, University of Wollongong, Australia.
authors.forename: Gregory E
authors.initials: GE
authors.lastname: Peoples
authors.affiliation: Early Start Research Institute, Faculty of Social Sciences, University of Wollongong, Australia.
authors.forename: Rachel A
authors.initials: RA
authors.lastname: Jones
authors.affiliation: University of Strathclyde, School of Psychological Sciences and Health, Scotland.
authors.forename: Xanne
authors.initials: X
authors.lastname: Janssen
authors.affiliation: Early Start Research Institute, Faculty of Social Sciences, University of Wollongong, Australia.
authors.forename: Dylan P
authors.initials: DP
authors.lastname: Cliff
mesh_terms: D061725:Accelerometry / Q000379:methods*; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D004734:Energy Metabolism / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008991:Monitoring, Physiologic / Q000379:methods; D009043:Motor Activity / Q000502:physiology*; D010101:Oxygen Consumption / Q000502:physiology; D015203:Reproducibility of Results
keywords: Accelerometry; Calorimetry; Energy expenditure; Physical activity; Validation study