Related Experiment Video
Updated: Feb 28, 2026
Home-Based Monitor for Gait and Activity Analysis
Published on: August 8, 2019
Accuracy and precision of smartphone applications and commercially available motion sensors in multiple sclerosis
Julia M Balto1, Dominique L Kinnett-Hopkins1, Robert W Motl1
1Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, IL, USA.
Background:
There is increased interest in the application of smartphone applications and wearable motion sensors among multiple sclerosis (MS) patients.
Objective:
This study examined the accuracy and precision of common smartphone applications and motion sensors for measuring steps taken by MS patients while walking on a treadmill.
Methods:
Forty-five MS patients (Expanded Disability Status Scale (EDSS) = 1.0-5.0) underwent two 500-step walking trials at comfortable walking speed on a treadmill. Participants wore five motion sensors: the Digi-Walker SW-200 pedometer (Yamax), the UP2 and UP Move (Jawbone), and the Flex and One (Fitbit). The smartphone applications were Health (Apple), Health Mate (Withings), and Moves (ProtoGeo Oy).
Results:
The Fitbit One had the best absolute (mean = 490.6 steps, 95% confidence interval (CI) = 485.6-495.5 steps) and relative accuracy (1.9% error), and absolute (SD = 16.4) and relative precision (coefficient of variation (CV) = 0.0), for the first 500-step walking trial; this was repeated with the second trial. Relative accuracy was correlated with slower walking speed for the first (r-.53) and second (r-.53) trials.
Conclusion:
The results suggest that the waist-worn Fitbit One is the most precise and accurate sensor for measuring steps when walking on a treadmill, but future research is needed (testing the device across a broader range of disability, at different speeds, and in real-life walking conditions) before inclusion in clinical research and practice with MS patients.
