ArticleScientific reports2025
Phenotyping and characterising gait profiles of people with multiple sclerosis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Immersive Virtual Reality Assessment in Multiple Sclerosis: Patient-Reported Experience and Correlates.Brain sciences · 2026Article
- User-centered design and formative evaluation of a gait dashboard for multidimensional walking assessment in multiple sclerosis.Frontiers in digital health · 2026Article
- Jump assessment on a force plate-an approach to quantify subtle lower limb neuromuscular deficits in people with multiple sclerosis.Frontiers in neurologyReview
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gait disorders are among the most disabling symptoms in people with multiple sclerosis (pwMS), substantially affecting quality of life, autonomy, and participation. The Expanded Disability Status Scale (EDSS) captures impairments -particularly pyramidal, cerebellar and sensory- that influence gait patterns. Quantitative gait analysis enables objective exploration of these patterns supporting personalised strategies. This study aimed to characterise gait profiles in pwMS based on EDSS-derived functional scores. In this cross-sectional study at University Hospital Dresden, 204 pwMS and 237 healthy controls underwent instrumented gait assessments under self-selected, fast, and dual-task conditions. PwMS were categorised into pyramidal, cerebellar, or sensory gait pattern groups based on EDSS functional system scores. Spatiotemporal gait parameters were analysed using generalised linear models adjusted for age, gender, and body mass index. Sensory gait patterns were observed in 57.8% of pwMS, pyramidal in 27.9%, and cerebellar in 14.2%. Significant group differences emerged across all walking conditions. Ataxic gait showed reduced speed and increased step and stride variability. Sensory patterns featured higher speed, longer steps, and increased cadence. Pyramidal patterns resembled ataxic ones but differed under fast walking. EDSS-based functional deficits correspond to distinct MS-specific gait profiles. Multidimensional clinical gait phenotyping provides actionable insights for tailoring rehabilitation and monitoring mobility outcomes in pwMS.
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