title: Automatic identification of physical activity types and sedentary behaviors from triaxial accelerometer: laboratory-based calibrations are not enough.
abstract: "Objective" methods to monitor physical activity and sedentary patterns in free-living conditions are necessary to further our understanding of their impacts on health. In recent years, many software solutions capable of automatically identifying activity types from portable accelerometry data have been developed, with promising results in controlled conditions, but virtually no reports on field tests. An automatic classification algorithm initially developed using laboratory-acquired data (59 subjects engaging in a set of 24 standardized activities) to discriminate between 8 activity classes (lying, slouching, sitting, standing, walking, running, and cycling) was applied to data collected in the field. Twenty volunteers equipped with a hip-worn triaxial accelerometer performed at their own pace an activity set that included, among others, activities such as walking the streets, running, cycling, and taking the bus. Performances of the laboratory-calibrated classification algorithm were compared with those of an alternative version of the same model including field-collected data in the learning set. Despite good results in laboratory conditions, the performances of the laboratory-calibrated algorithm (assessed by confusion matrices) decreased for several activities when applied to free-living data. Recalibrating the algorithm with data closer to real-life conditions and from an independent group of subjects proved useful, especially for the detection of sedentary behaviors while in transports, thereby improving the detection of overall sitting (sensitivity: laboratory model = 24.9%; recalibrated model = 95.7%). Automatic identification methods should be developed using data acquired in free-living conditions rather than data from standardized laboratory activity sets only, and their limits carefully tested before they are used in field studies.
authors.affiliation: CarMeN INSERM U1060, University of Lyon 1, INRA U1235, Centre de Recherche en Nutrition Humaine Rhône-Alpes, Centre Européen pour la Nutrition & la Santé, Pierre-Bénite, France;
authors.forename: Thomas
authors.initials: T
authors.lastname: Bastian
authors.affiliation: CarMeN INSERM U1060, University of Lyon 1, INRA U1235, Centre de Recherche en Nutrition Humaine Rhône-Alpes, Centre Européen pour la Nutrition & la Santé, Pierre-Bénite, France;
authors.forename: Aurélia
authors.initials: A
authors.lastname: Maire
authors.affiliation: CarMeN INSERM U1060, University of Lyon 1, INRA U1235, Centre de Recherche en Nutrition Humaine Rhône-Alpes, Centre Européen pour la Nutrition & la Santé, Pierre-Bénite, France;
authors.forename: Julien
authors.initials: J
authors.lastname: Dugas
authors.affiliation: University of Grenoble Alpes, Grenoble, France; Commissariat à l'Énergie Atomique, Leti, Département Microtechnologies pour la Biologie et la Santé, Laboratoire Électronique et Systèmes pour la Santé, MINATEC, Grenoble, France;
authors.forename: Abbas
authors.initials: A
authors.lastname: Ataya
authors.affiliation: CarMeN INSERM U1060, University of Lyon 1, INRA U1235, Centre de Recherche en Nutrition Humaine Rhône-Alpes, Centre Européen pour la Nutrition & la Santé, Pierre-Bénite, France;
authors.forename: Clément
authors.initials: C
authors.lastname: Villars
authors.affiliation: University of Grenoble Alpes, Grenoble, France; Commissariat à l'Énergie Atomique, Leti, Département Microtechnologies pour la Biologie et la Santé, Laboratoire Électronique et Systèmes pour la Santé, MINATEC, Grenoble, France;
authors.forename: Florence
authors.initials: F
authors.lastname: Gris
authors.affiliation: Movea, Grenoble, France;
authors.forename: Emilie
authors.initials: E
authors.lastname: Perrin
authors.affiliation: Movea, Grenoble, France;
authors.forename: Yanis
authors.initials: Y
authors.lastname: Caritu
authors.affiliation: University of Grenoble Alpes, Grenoble, France; Commissariat à l'Énergie Atomique, Leti, Département Microtechnologies pour la Biologie et la Santé, Laboratoire Électronique et Systèmes pour la Santé, MINATEC, Grenoble, France;
authors.forename: Maeva
authors.initials: M
authors.lastname: Doron
authors.affiliation: Hubert Curien Pluridisciplinary Institute, Department of Ecology, Physiology and Ethology, University of Strasbourg, UMR CNRS 7178, Strasbourg, France; and.
authors.forename: Stéphane
authors.initials: S
authors.lastname: Blanc
authors.affiliation: University of Grenoble Alpes, Grenoble, France; Commissariat à l'Énergie Atomique, Leti, Département Microtechnologies pour la Biologie et la Santé, Laboratoire Électronique et Systèmes pour la Santé, MINATEC, Grenoble, France;
authors.forename: Pierre
authors.initials: P
authors.lastname: Jallon
authors.affiliation: CarMeN INSERM U1060, University of Lyon 1, INRA U1235, Centre de Recherche en Nutrition Humaine Rhône-Alpes, Centre Européen pour la Nutrition & la Santé, Pierre-Bénite, France; Service d'Endocrinologie, Diabètes, Nutrition, Centre Hospitalier Lyon Sud, Pierre-Bénite, France Chantal.Simon@univ-lyon1.fr.
authors.forename: Chantal
authors.initials: C
authors.lastname: Simon
mesh_terms: D061725:Accelerometry / Q000379:methods; D000328:Adult; D000465:Algorithms; D002138:Calibration; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods; D009043:Motor Activity / Q000502:physiology*; D011187:Posture / Q000502:physiology*; D057185:Sedentary Behavior; D012984:Software; D055815:Young Adult
keywords: actimetry; field study; machine learning and classification methods; physical activity; sedentary behaviors