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The application of principal component analysis to characterize gait and its association with falls in multiple
Andrew S Monaghan1, Jessie M Huisinga2, Daniel S Peterson3,4
1College of Health Solutions, Arizona State University, 425 N 5th St., Phoenix, AZ, 85282, USA.
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.
Insights
People with multiple sclerosis experience gait problems linked to falls. A new model identifies key gait domains, showing fallers have slower and more asymmetrical walking patterns.
Area of Science:
- Neurology
- Biomechanics
- Rehabilitation Science
Background:
- Gait impairments in people with multiple sclerosis (PwMS) are a significant factor in falls.
- Existing gait outcome reporting methods can be redundant.
- There is a need for a standardized, MS-specific gait model.
Purpose of the Study:
- To develop a novel, MS-specific gait model using principal component analysis (PCA).
- To compare gait domains between individuals with MS who fall (MS-F) and those who do not (MS-NF).
- To explore correlations between gait domains and cognitive, clinical, and quality-of-life measures.
Main Methods:
- 122 people with relapsing-remitting MS and 45 controls underwent timed up-and-go trials with inertial sensors.
- 21 gait parameters were analyzed using PCA to identify distinct gait domains.
- Statistical comparisons were made between MS-F and MS-NF groups, and correlations were calculated.
Main Results:
- Six gait domains were identified: pace, rhythm, variability, asymmetry, anterior-posterior dynamic stability, and medial-lateral dynamic stability, explaining 79.15% of gait variance.
- PwMS showed slower pace, greater variability, and increased medial-lateral trunk motion compared to controls.
- MS-F demonstrated significantly worse (slower and more asymmetrical) pace and asymmetry domains compared to MS-NF.
Conclusions:
- A six-component, MS-specific gait model was successfully developed.
- Gait deficits, particularly in pace and asymmetry, are more pronounced in MS fallers.
- This model can reduce redundancy in gait outcome reporting and guide targeted interventions for PwMS.
