ArticleScientific reports2021
The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Characterizing gait in people with multiple sclerosis using digital data from smartphone sensors: A proposed framework.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Pooled it
- Gait asymmetry across frailty-status groups in older adults: clinical and biomechanical evidence from 3D gait analysis.Annals of medicine · 2026Article
- Laboratory-based turning performance during walking in people with mild cognitive impairment and dementia.Journal of Alzheimer's disease : JAD · 2026Article
- Gait adaptations to walker-assisted locomotion in elderly: a principal component analysis of spatiotemporal and kinematic parameters.Scientific reports · 2026Article
- User-centered design and formative evaluation of a gait dashboard for multidimensional walking assessment in multiple sclerosis.Frontiers in digital health · 2026Article
- Phenotyping and characterising gait profiles of people with multiple sclerosis.Scientific reports · 2025Article
- Fall history moderates the relationship between concern about falling and reactive stepping performance in people with multiple sclerosis.Neuroscience · 2025Article
- Non-contact, non-visual, multi-person hallway gait monitoring.Scientific reports · 2025Article
- Kinematic and Kinetic Gait Principal Component Domains in Older Adults With and Without Functional Disability: A Cross-Sectional Study.Journal of functional morphology and kinesiology · 2025Article
- Walk Longer! Using Wearable Inertial Sensors to Uncover Which Gait Aspects Should Be Treated to Increase Walking Endurance in People with Multiple Sclerosis.Sensors (Basel, Switzerland) · 2024Article
- Motion acquisition of gait characteristics one week after total hip arthroplasty: a factor analysis.Archives of orthopaedic and trauma surgery · 2024Article
- Using the Instrumented Sway System (ISway) to Identify and Compare Balance Domain Deficits in People With Multiple Sclerosis.Archives of physical medicine and rehabilitation · 2023Article
- Examining the Relationship Between Reactive Stepping Outcomes and Falls in People With Multiple Sclerosis.Physical therapy · 2022Article
- Role of artificial intelligence in MS clinical practice.NeuroImage. Clinical · 2022Review
- Innovations in Multiple Sclerosis Care: The Impact of Artificial Intelligence via Machine Learning on Clinical Research and Decision-Making.International journal of MS careArticle
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
People with multiple sclerosis (PwMS) demonstrate gait impairments that are related to falls. However, redundancy exists when reporting gait outcomes. This study aimed to develop an MS-specific model of gait and examine differences between fallers and non-fallers. 122 people with relapsing-remitting MS and 45 controls performed 3 timed up-and-go trials wearing inertial sensors. 21 gait parameters were entered into a principal component analysis (PCA). The PCA-derived gait domains were compared between MS fallers (MS-F) and MS non-fallers (MS-NF) and correlated to cognitive, clinical, and quality-of-life outcomes. Six distinct gait domains were identified: pace, rhythm, variability, asymmetry, anterior-posterior dynamic stability, and medial-lateral dynamic stability, explaining 79.15% of gait variance. PwMS exhibited a slower pace, larger variability, and increased medial-lateral trunk motion compared to controls (p < 0.05). The pace and asymmetry domains were significantly worse (i.e., slower and asymmetrical) in MS-F than MS-NF (p < 0.001 and p = 0.03, respectively). Fear of falling, cognitive performance, and functional mobility were associated with a slower gait (p < 0.05). This study identified a six-component, MS-specific gait model, demonstrating that PwMS, particularly fallers, exhibit deficits in pace and asymmetry. Findings may help reduce redundancy when reporting gait outcomes and inform interventions targeting specific gait domains.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.