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Assessing nonlinear gait characteristics in multiple sclerosis: Insights from a systematic review
José M Gavira-Seoane1, Almudena Martínez-Sánchez2, Francisco J Dominguez-Muñoz2
1Grupo de Investigación en Actividad Física, Calidad de Vida y Salud (AFYCAV), Didáctica de la Expresión Musical, Plástica y Corporal, Facultad de Ciencias del Deporte, Universidad de Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain.
Nonlinear gait analysis, especially Lyapunov exponents, shows promise for detecting motor control changes in multiple sclerosis (MS) patients. Further research is needed to standardize methods for clinical use.
Area of Science:
- Neuroscience
- Biomechanical Engineering
- Rehabilitation Science
Background:
- Multiple sclerosis (MS) is a chronic neurodegenerative disease impacting gait and independence.
- Nonlinear gait analysis offers potential insights into motor control deficits in MS.
- Existing research on nonlinear gait variables in MS is limited and fragmented.
Purpose of the Study:
- To systematically review and synthesize research on nonlinear gait variables in individuals with multiple sclerosis.
- To focus on specific nonlinear metrics: entropy, Lyapunov exponents, and detrended fluctuation analysis.
- To assess the current evidence for nonlinear gait analysis in understanding MS-related gait alterations.
Main Methods:
- Systematic review adhering to PRISMA guidelines.
- Searches conducted in PubMed and Web of Science databases.
- Inclusion of studies comparing MS patients and healthy controls using treadmill or overground walking.
- Assessment of methodological quality using the JBI Checklist.
Main Results:
- Ten studies involving 430 MS patients and 212 controls met inclusion criteria.
- Lyapunov exponent was the most frequently studied nonlinear variable.
- Five of nine studies found significant differences, with three indicating higher Lyapunov exponents in MS patients.
- Entropy and detrended fluctuation analysis showed less consistent results.
Conclusions:
- Nonlinear gait metrics, particularly the Lyapunov exponent, may indicate altered gait dynamics in MS, even in minimally disabled individuals.
- Factors like fatigue, motor control changes, and methodological variations may influence these metrics.
- Limited and heterogeneous evidence necessitates future studies with standardized reporting for clinical application.
