How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study

JMIR Mhealth Uhealth. 2019 Jan 9;7(1):e10418. doi: 10.2196/10418.


Background: Smartphones have great potential for monitoring physical activity. Although a previous laboratory-based study reported that smartphone apps were accurate for tracking step counts, little evidence on their accuracy in free-living conditions currently exists.

Objective: We aimed to investigate the accuracy of step counts measured using iPhone in the real world.

Methods: We recruited a convenience sample of 54 adults (mean age 31 [SD 10] years) who owned an iPhone and analyzed data collected in 2016 and 2017. Step count was simultaneously measured using a validated pedometer (Kenz Lifecorder) and the iPhone. Participants were asked to carry and use their own iPhones as they typically would while wearing a pedometer on the waist for 7 consecutive days during waking hours. To assess the agreement between the two measurements, we calculated Spearman correlation coefficients and prepared a Bland-Altman plot.

Results: The mean step count measured using the iPhone was 9253 (3787) steps per day, significantly lower by 12% (1277/10,530) than that measured using the pedometer, 10,530 (3490) steps per day (P<.001). The Spearman correlation coefficient between devices was 0.78 (P<.001). The largest underestimation of steps by the iPhone was observed among those who reported to have seldom carried their iPhones (seldom carry: mean -3036, SD 2990, steps/day; sometimes carry: mean -1424, SD 2619, steps/day; and almost always carry: mean -929, SD 1443, steps/day; P for linear trend=.08).

Conclusions: Smartphones may be of practical use to individuals, clinicians, and researchers for monitoring physical activity. However, their data on step counts should be interpreted cautiously because of the possibility of underestimation due to noncarrying time.

Keywords: epidemiology; free-living conditions; mobile phone; pedometer; physical activity; population; step count; validation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Actigraphy / instrumentation
  • Adult
  • Cross-Sectional Studies
  • Exercise
  • Female
  • Humans
  • Male
  • Monitoring, Ambulatory / instrumentation*
  • Monitoring, Ambulatory / methods
  • Monitoring, Ambulatory / standards
  • Smartphone / standards*
  • Smartphone / statistics & numerical data
  • Validation Studies as Topic
  • Walking / physiology
  • Walking / statistics & numerical data*