title: Validation of the SenseWear mini armband in children during semi-structure activity settings.
abstract: OBJECTIVE
  The purpose of the study is to evaluate the validity of different SenseWear software (algorithms v5.2 vs. algorithm v2.2) for estimating energy expenditure (EE) in children.
  
  
  METHODS
  Original research.
  
  
  METHODS
  Forty-five children aged 7-13 years performed 12 randomly assigned activities (out of a set of 24) while wearing a SWA with simultaneous monitoring via portable calorimetry (IC). Each activity lasted 5min, with a 1min break between activities. The estimated EE values from the SWA were compared to the measured EE values from the IC using 3-way (Method×Algorithm×Activity) mixed model ANOVA.
  
  
  RESULTS
  The analyses revealed a significant method (IC vs. SWA)×Algorithm (v5.2 vs. v2.2) interaction, with significantly smaller errors (IC-SWA) for the newer v5.2 algorithms (0.25±0.09kcalmin(-1)) than the older v2.2 algorithms (1.04±0.09kcalmin(-1)). The mean absolute percent error (MAPE) was 17.0±12.1% for SWA5.2 algorithm and 31.4±11.1% for SWA2.2 algorithm. The v5.2 algorithms yielded non-significant (p>0.5) differences in EE estimates for most of the walking related activities as well as for stationary cycling at moderate intensity (MAPE=14.5%).
  
  
  CONCLUSIONS
  The smaller errors in estimated EE with the SenseWear v5.2 algorithms (compared to v2.2) demonstrate continued incremental improvements in estimates of EE for monitoring free-living activities in children.
authors.affiliation: School of Health, Physical Education and Recreation, University of Nebraska-Omaha, USA. Electronic address: jungminlee@unomaha.edu.
authors.forename: Jung-Min
authors.initials: JM
authors.lastname: Lee
authors.affiliation: Department of Kinesiology, College of Human Sciences, Iowa State University, USA.
authors.forename: Youngwon
authors.initials: Y
authors.lastname: Kim
authors.affiliation: Department of Kinesiology, College of Human Sciences, Iowa State University, USA.
authors.forename: Yang
authors.initials: Y
authors.lastname: Bai
authors.affiliation: School of Nutrition & Health Promotion, Arizona State University, USA.
authors.forename: Glenn A
authors.initials: GA
authors.lastname: Gaesser
authors.affiliation: Department of Kinesiology, College of Human Sciences, Iowa State University, USA.
authors.forename: Gregory J
authors.initials: GJ
authors.lastname: Welk
mesh_terms: D061725:Accelerometry / Q000295:instrumentation*; D000293:Adolescent; D000465:Algorithms; D002153:Calorimetry, Indirect; D002648:Child; D004734:Energy Metabolism; D005260:Female; D006801:Humans; D008297:Male; D012984:Software
keywords: Accelerometer monitor; Children; Energy expenditure; Physical activity