Swing time symmetry & variability positively correlate with MSWS-12.

Double support time is positively associated with MSWS-12.

These metrics reflect the relevance of balance-related metrics.

Velocity, step and stride length negatively correlate with MSWS-12.

Gait velocity reflects perceived walking impairment in people with MS.

Mobility limitations are common among people with Multiple Sclerosis (MS), with gait impairments significantly impacting daily life. Gait assessments and patient-reported outcome measures are essential for assessing these gait impairments. However, it remains unclear which specific gait metrics best reflect the perceived walking impairments of people with MS. This study aimed to investigate the association between spatiotemporal gait metrics and the perceived walking impairments of people with MS.

A cross-sectional study with 23 people with MS was conducted. The patients’ perceived walking impairments were assessed by the 12- items MS walking scale (MSWS-12) and the gait metrics were measured by the sensor-based movement analysis system GAITrite® during the timed 25-foot walking test. To calculate the strength of the association between the gait metrics and the MSWS-12 the Spearman’s rank correlation coefficient was applied.

A positive correlation with the MSWS-12 score was found for mean double support time (rs=0.53, CI [0.12; 0.78]), swing time variability (rs=0.51, CI [0.09; 0–77]) and -symmetry (rs =0.53, CI [0.12; 0.78]), while mean step length (rs =-0.54, CI [-0.79; -0.13]), mean stride length (rs =-0.53, CI [-0.78; -0.12]) and gait velocity (rs =-0.60, CI [-0.82; -0.21]) showed a negative correlation.

Velocity remains a valuable metric, reflecting perceived walking impairments of people with MS. The findings to the association between the patient perceived walking impairments and the gait metrics mean double support time, swing time symmetry and swing time variability may highlight the relevance of balance-related metrics in assessing self-perceived walking impairments.

Multiple sclerosis

Gait metrics

Perceived impairments

Sensor-based analysis

Clinical assessment

© 2025 The Authors. Published by Elsevier B.V.