http://orcid.org/0000-0002-9190-7147
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ABSTRACT
Several attempts have been made to demonstrate the accuracy of the iPhone pedometer function in laboratory test conditions. However, no studies have attempted to evaluate evidence of convergent validity of the iPhone step counts as a surveillance tool in the field. This study takes a pragmatic approach to evaluating Health application derived iPhone step counts by measuring accuracy of a standardized criterion iPhone SE and a heterogeneous sample of participant owned iPhones (6 or newer) in a laboratory condition, as well as comparing personal iPhones to accelerometer derived steps in a free-living test. During lab tests, criterion and personal iPhones differed from manually counted steps by a mean bias of less than ±5% when walking at 5km/h, 7.5km/h and 10km/h on a treadmill, which is generally considered acceptable for pedometers. In the free-living condition steps differed by a mean bias of 21.5% or 1340 steps/day when averaged across observation days. Researchers should be cautioned in considering the use of iPhone models as a research grade pedometer for physical activity surveillance or evaluation, likely due to the iPhone not being continually carried by participants; if compliance can be maximized then the iPhone might be suitable.
Acknowledgements
We would like to extend our sincere thanks to Dr. Eli Puterman for the use of his laboratory and treadmill, and Ben Hives for coordinating access to the laboratory.
Disclosure statement
No potential conflict of interest was reported by the authors.
Geolocation information
University of British Columbia, Copp Building Room 4008, 2146 Health Sciences Mall, Vancouver, BC, Canada, V6T 1Z3
Notes
1 CM = “Core Motion” a designation for variables calculated by the motion co-processor.