The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions

Shaoxiong Sun, Amos A Folarin, Yuezhou Zhang, Nicholas Cummins, Shuo Liu, Callum Stewart, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Petroula Laiou, Heet Sankesara, Gloria Dalla Costa, Letizia Leocani, Per Soelberg Sørensen, Melinda Magyari, Ana Isabel Guerrero, Ana Zabalza, Srinivasan Vairavan, Raquel Bailon, Sara SimblettInez Myin-Germeys, Aki Rintala, Til Wykes, Vaibhav A Narayan, Matthew Hotopf, Giancarlo Comi, Richard JB Dobson, RADAR-CNS consortium

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
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Background and objectives
Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to evaluate the progression of MS. Yet, it has limitations such as the need for a clinical visit and a proper walkway. The widespread use of wearable devices capable of depicting patients’ activity profiles has the potential to assess the level of MS-induced disability in free-living conditions.

In this work, we extracted 96 features in different temporal granularities (from minute-level to day-level) from wearable data and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10 months’ duration. We combined these features with participants’ demographics using three regression models including elastic net, gradient boosted trees and random forest. In addition, we quantified the individual feature's contribution using feature importance in these regression models, linear mixed-effects models, generalized estimating equations, and correlation-based feature selection (CFS).

The results showed promising estimation performance with R2 of 0.30, which was derived using random forest after CFS. This model was able to distinguish the participants with low disability from those with high disability. Furthermore, we observed that the minute-level (≤ 8 minutes) step count, particularly those capturing the upper end of the step count distribution, had a stronger association with 6MWT. The use of a walking aid was indicative of ambulatory function measured through 6MWT.

This study demonstrates the utility of wearables devices in assessing ambulatory impairments in people with MS in free-living conditions and provides a basis for future investigation into the clinical relevance.
Original languageEnglish
JournalComputer Methods and Programs in Biomedicine
Publication statusPublished - Dec 2022


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