Accuracy and precision of smartphone applications and commercially available motion sensors in multiple sclerosis

Mult Scler J Exp Transl Clin. 2016 Mar 4:2:2055217316634754. doi: 10.1177/2055217316634754. eCollection 2016 Jan-Dec.


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 (rs = -.53) and second (rs = -.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.

Keywords: Fitbit; MS; Motion sensors; smartphone applications; steps.