title: A universal, accurate intensity-based classification of different physical activities using raw data of accelerometer.
abstract: OBJECTIVE
  Accelerometers are increasingly used for objective assessment of physical activity. However, because of lack of the proprietary analysis algorithms, direct comparisons between accelerometer brands are difficult. In this study, we propose and evaluate open source methods for commensurate assessment of raw accelerometer data irrespective of the brand.
  
  
  METHODS
  Twenty-one participants carried simultaneously three different tri-axial accelerometers on their waist during five different sedentary activities and five different intensity levels of bipedal movement from slow walking to running. Several time and frequency domain traits were calculated from the measured raw data, and their performance in classifying the activities was compared.
  
  
  RESULTS
  Of the several traits, the mean amplitude deviation (MAD) provided consistently the best performance in separating the sedentary activities and different speeds of bipedal movement from each other. Most importantly, the universal cut-off limits based on MAD classified sedentary activities and different intensity levels of walking and running equally well for all three accelerometer brands and reached at least 97% sensitivity and specificity in each case.
  
  
  CONCLUSIONS
  Irrespective of the accelerometer brand, a simply calculable MAD with universal cut-off limits provides a universal method to evaluate physical activity and sedentary behaviour using raw accelerometer data. A broader application of the present approach is expected to render different accelerometer studies directly comparable with each other.
authors.affiliation: UKK Institute, Tampere, Finland.
authors.forename: Henri
authors.initials: H
authors.lastname: Vähä-Ypyä
authors.affiliation: UKK Institute, Tampere, Finland.
authors.forename: Tommi
authors.initials: T
authors.lastname: Vasankari
authors.affiliation: UKK Institute, Tampere, Finland.
authors.forename: Pauliina
authors.initials: P
authors.lastname: Husu
authors.affiliation: UKK Institute, Tampere, Finland.
authors.forename: Jaana
authors.initials: J
authors.lastname: Suni
authors.affiliation: UKK Institute, Tampere, Finland.
authors.forename: Harri
authors.initials: H
authors.lastname: Sievänen
mesh_terms: D061725:Accelerometry / Q000295:instrumentation* / Q000379:methods; D056044:Actigraphy / Q000295:instrumentation* / Q000379:methods; D000328:Adult; D000465:Algorithms; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D006801:Humans; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods; D009043:Motor Activity / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D005082:Physical Exertion / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: accelerometer; objective assessment; physical activity; reliability; sedentary behaviour