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

Abstract

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.