title: Validation of Physical Activity Tracking via Android Smartphones Compared to ActiGraph Accelerometer: Laboratory-Based and Free-Living Validation Studies.
abstract: BACKGROUND
  There is increasing interest in using smartphones as stand-alone physical activity monitors via their built-in accelerometers, but there is presently limited data on the validity of this approach.
  
  
  OBJECTIVE
  The purpose of this work was to determine the validity and reliability of 3 Android smartphones for measuring physical activity among midlife and older adults.
  
  
  METHODS
  A laboratory (study 1) and a free-living (study 2) protocol were conducted. In study 1, individuals engaged in prescribed activities including sedentary (eg, sitting), light (sweeping), moderate (eg, walking 3 mph on a treadmill), and vigorous (eg, jogging 5 mph on a treadmill) activity over a 2-hour period wearing both an ActiGraph and 3 Android smartphones (ie, HTC MyTouch, Google Nexus One, and Motorola Cliq). In the free-living study, individuals engaged in usual daily activities over 7 days while wearing an Android smartphone (Google Nexus One) and an ActiGraph.
  
  
  RESULTS
  Study 1 included 15 participants (age: mean 55.5, SD 6.6 years; women: 56%, 8/15). Correlations between the ActiGraph and the 3 phones were strong to very strong (ρ=.77-.82). Further, after excluding bicycling and standing, cut-point derived classifications of activities yielded a high percentage of activities classified correctly according to intensity level (eg, 78%-91% by phone) that were similar to the ActiGraph's percent correctly classified (ie, 91%). Study 2 included 23 participants (age: mean 57.0, SD 6.4 years; women: 74%, 17/23). Within the free-living context, results suggested a moderate correlation (ie, ρ=.59, P<.001) between the raw ActiGraph counts/minute and the phone's raw counts/minute and a strong correlation on minutes of moderate-to-vigorous physical activity (MVPA; ie, ρ=.67, P<.001). Results from Bland-Altman plots suggested close mean absolute estimates of sedentary (mean difference=-26 min/day of sedentary behavior) and MVPA (mean difference=-1.3 min/day of MVPA) although there was large variation.
  
  
  CONCLUSIONS
  Overall, results suggest that an Android smartphone can provide comparable estimates of physical activity to an ActiGraph in both a laboratory-based and free-living context for estimating sedentary and MVPA and that different Android smartphones may reliably confer similar estimates.
authors.affiliation: Arizona State University, School of Nutrition and Health Promotion, Phoenix, AZ, United States. ehekler@asu.edu.
authors.forename: Eric B
authors.identifier: http://orcid.org/0000-0002-7434-0775
authors.initials: EB
authors.lastname: Hekler
authors.forename: Matthew P
authors.identifier: http://orcid.org/0000-0002-5130-3162
authors.initials: MP
authors.lastname: Buman
authors.forename: Lauren
authors.identifier: http://orcid.org/0000-0002-7084-8723
authors.initials: L
authors.lastname: Grieco
authors.forename: Mary
authors.identifier: http://orcid.org/0000-0002-0380-1650
authors.initials: M
authors.lastname: Rosenberger
authors.forename: Sandra J
authors.identifier: http://orcid.org/0000-0002-4930-2005
authors.initials: SJ
authors.lastname: Winter
authors.forename: William
authors.identifier: http://orcid.org/0000-0002-7079-055X
authors.initials: W
authors.lastname: Haskell
authors.forename: Abby C
authors.identifier: http://orcid.org/0000-0002-7949-8811
authors.initials: AC
authors.lastname: King
keywords: accelerometry; cell phones; motor activity; telemedicine; validation studies