Gait stability at early stages of multiple sclerosis using different data sources

Area of Science:

• Neurology
• Biomechanics
• Rehabilitation Science

Background:

• Early-stage multiple sclerosis (MS) can cause subtle balance deficits impacting gait stability.
• Variations in sensor technology and placement can yield inconsistent results in stability assessments, complicating comparisons across studies.

Purpose of the Study:

• To investigate whether people with multiple sclerosis (PwMS) exhibit reduced gait stability compared to healthy controls.
• To determine if the location and type of data used to calculate stability metrics influence these comparisons.

Main Methods:

• Thirty PwMS and 15 healthy controls walked on a treadmill at 1.2 m/s.
• 3D acceleration data was collected from sacrum, shoulder, and cervical markers, plus a sacrum-mounted accelerometer.
• The local divergence exponent was calculated for all four data sources, with ANOVA used to analyze group and data source effects.

Main Results:

• PwMS demonstrated significantly lower gait stability across all sensor types compared to controls.
• A significant effect of data source on stability was observed, with the sacrum accelerometer yielding lower local divergence exponent values.

Conclusions:

• Even individuals with MS and no clinically apparent gait impairments exhibit reduced walking stability.
• Standardization of sensor location and data source is crucial for consistent MS-related gait stability assessment.
• The local divergence exponent shows promise as a metric for monitoring gait instability progression in early MS stages.