Validating wearable step counts in multiple sclerosis research: a replication study.

INTRODUCTION: For people with multiple sclerosis (MS), mobility impairment is common and a significant contributor to reduced quality of life. With advancements in wearable technology, step count data has emerged as a promising method to track mobility and monitor functional decline. However, studies comparing the replicability of wearable mobility data using varying devices remain limited in MS populations. METHODS: This study investigates the reliability of step count data and its associations with clinical outcomes in MS patients using two independent cohorts with different wearable devices: California (CA) (n = 97 Fitbit wrist sensor, 4-week wear) and Virginia (VA) (n = 61; ActiGraph hip sensor, 7-day wear). We analyzed correlations between average daily step counts and common MS clinical measures [disability: Expanded Disability Status Scale (EDSS); walking speed: Timed 25-Foot Walk (T25FW)] as well as patient-reported outcomes (12-item MS walking scale, MSWS-12, Modified Fatigue Impact score, MFIS). RESULTS: Analysis of the VA cohort revealed similar average daily step counts to those seen in the CA cohort (6,010 vs. 5,478 steps/day). Step count variability (standard deviation) decreased with increasing EDSS in both cohorts. Step counts in the VA cohort were significantly correlated with EDSS (r = -0.34), T25FW (r = -0.58), MSWS-12 (r = -0.57), and MFIS (r = -0.45), similar to findings from the CA cohort. Additionally, within-subject reliability over 7 days was moderate (ICC = 0.599), with high correlations between 4-day and 7-day averages (r ≥ 0.98). DISCUSSION: The step count analyses from two different wearable devices show replicable associations with clinical and patient-reported outcomes in MS, highlighting their promise as digital biomarkers for clinical monitoring and care, rehabilitation, and patient self-management.