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.