Gait asymmetry assessment through Eigen-Gait components on dissimilarity maps

Area of Science:

• Biomechanics
• Neurology
• Rehabilitation Science

Background:

• Neurological diseases significantly impair gait, affecting lower limb coordination.
• Assessing gait deviations is crucial for monitoring motor function and patient rehabilitation progress.

Purpose of the Study:

• To introduce a novel method for quantifying bilateral gait asymmetry in patients with neurological disorders.
• To develop a comprehensive score reflecting gait deviations and asymmetry for clinical monitoring.

Main Methods:

• Developed a gait dissimilarity map to represent bilateral gait signals and their spatiotemporal dynamics.
• Constructed a healthy gait model using Singular Value Decomposition to identify gait symmetry eigenvectors.
• Computed the Eigen-Gait Asymmetry Index (EGAI) by projecting patient gait data onto the healthy gait model.

Main Results:

• Patients with neurological gait disorders exhibited significantly higher EGAI values (9.73 ±2.16) compared to healthy controls (3.86 ±0.9).
• Hemiparesis patients showed the highest EGAI, indicating more asymmetrical gait due to unilateral body impact.
• EGAI trends were consistent across knee, hip, ankle, and pelvis joints in the sagittal plane.

Conclusions:

• The Eigen-Gait Asymmetry Index (EGAI) effectively quantifies gait asymmetry induced by neurological diseases.
• This innovative bilateral assessment method provides a more comprehensive understanding of gait deviations than traditional unilateral measures.
• EGAI serves as a precise and effective tool for clinicians to monitor patient progress during rehabilitation.