title: Comparability of measured acceleration from accelerometry-based activity monitors.
abstract: BACKGROUND
  Accelerometers that provide triaxial measured acceleration data are now available. However, equivalence of output between brands cannot be assumed and testing is necessary to determine whether features of the acceleration signal are interchangeable.
  
  
  OBJECTIVE
  This study aimed to establish the equivalence of output between two brands of monitor in a laboratory and in a free-living environment.
  
  
  METHODS
  For part 1, 38 adults performed nine laboratory-based activities while wearing an ActiGraph GT3X+ and GENEActiv (Gravity Estimator of Normal Everyday Activity) at the hip. For part 2, 58 children age 10-12 yr wore a GT3X+ and GENEActiv at the hip for 7 d in a free-living setting.
  
  
  RESULTS
  For part 1, the magnitude of time domain features from the GENEActiv was greater than that from the GT3X+. However, frequency domain features compared well, with perfect agreement of the dominant frequency for 97%-100% of participants for most activities. For part 2, mean daily acceleration measured by the two brands was correlated (r = 0.93, P < 0.001, respectively) but the magnitude was approximately 15% lower for the GT3X+ than that for the GENEActiv at the hip.
  
  
  CONCLUSIONS
  Frequency domain-based classification algorithms should be transferable between monitors, and it should be possible to apply time domain-based classification algorithms developed for one device to the other by applying an affine conversion on the measured acceleration values. The strong relation between accelerations measured by the two brands suggests that habitual activity level and activity patterns assessed by the GENE and GT3X+ may compare well if analyzed appropriately.
authors.affiliation: 1Health and Use of Time Group, Sansom Institute for Health Research, Division of Health Sciences, University of South Australia, Adelaide, AUSTRALIA; 2Exercise for Health and Human Performance Group, Sansom Institute for Health Research, Division of Health Sciences, University of South Australia, Adelaide, AUSTRALIA; 3Institute for Ageing and Health, Faculty of Medicine, Newcastle University, Newcastle, UNITED KINGDOM; and 4Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, Exeter, UNITED KINGDOM.
authors.forename: Alex V
authors.initials: AV
authors.lastname: Rowlands
authors.forename: FranÇois
authors.initials: F
authors.lastname: Fraysse
authors.forename: Mike
authors.initials: M
authors.lastname: Catt
authors.forename: Victoria H
authors.initials: VH
authors.lastname: Stiles
authors.forename: Rebecca M
authors.initials: RM
authors.lastname: Stanley
authors.forename: Roger G
authors.initials: RG
authors.lastname: Eston
authors.forename: Tim S
authors.initials: TS
authors.lastname: Olds
mesh_terms: D000054:Acceleration; D061725:Accelerometry / Q000295:instrumentation*; D000328:Adult; D000465:Algorithms; D002648:Child; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted