Video-based 2D markerless gait analysis in people with multiple sclerosis.

Area of Science:

• Neuroscience
• Biomechanical Engineering
• Rehabilitation Medicine

Background:

• Multiple Sclerosis (MS) is a neurodegenerative disease causing progressive gait impairment, impacting mobility and independence.
• The Expanded Disability Status Scale (EDSS) is a standard measure, but may not capture subtle gait alterations.
• Quantitative gait analysis offers complementary insights into motor function in MS.

Purpose of the Study:

• To assess the feasibility of a markerless, 2D video-based approach for quantitative gait analysis in MS patients.
• To determine if gait parameters derived from video analysis correlate with overall disability levels (EDSS scores).

Main Methods:

• Twenty MS patients were recorded walking using a single standard video camera.
• A pose estimation algorithm extracted spatiotemporal parameters and lower-limb elevation angles.
• Statistical analyses examined the association between gait measures and EDSS scores.

Main Results:

• Normalized stride length and stride time significantly decreased with increasing disability.
• The range of motion for shank and foot elevation angles showed strong correlations with EDSS scores.
• Reduced range of motion in distal lower limb segments indicated greater disability.

Conclusions:

• Markerless 2D video analysis is a feasible, low-cost method for objective gait assessment in MS.
• Lower limb range of motion, especially in distal segments, serves as a sensitive indicator of gait impairment related to MS disability.
• This approach can provide valuable complementary data to the EDSS for monitoring MS progression.