Understanding the Physiological Significance of Four Inertial Gait Features in Multiple Sclerosis.

Area of Science:

• Biomechanics
• Neurology
• Digital Health

Background:

• Gait impairment is a common symptom in multiple sclerosis (MS), affecting mobility and quality of life.
• Current clinical research primarily relies on walking speed to measure gait impairment.
• Inertial gait features from wearable sensors offer potential for more comprehensive gait analysis in MS.

Purpose of the Study:

• To differentiate the physiological significance of four inertial gait features (DTW Score, Warp Score, KDE Peak, Causality Index) in multiple sclerosis.
• To facilitate the adoption of these features by clinical researchers for gait monitoring and analysis.
• To explore the potential application of these features in analyzing other forms of disability.

Main Methods:

• Utilized dynamic time warping (DTW) to compute DTW Score and Warp Score.
• Employed kernel density estimation (KDE) to derive the KDE Peak value.
• Calculated the Causality Index using the phase slope index between inertial signals.
• Applied factor analysis to clinical walking outcomes and correlated inertial measures with extracted factors.

Main Results:

• Statistically significant differences were found in the correlation coefficients of the inertial measures to the extracted clinical factors.
• These differences support the distinct physiological meaning of each inertial gait feature.
• The findings suggest that these features may play complementary roles in analyzing MS-related walking disability.

Conclusions:

• The four inertial gait features possess distinct physiological significance in the context of multiple sclerosis.
• These features offer a more nuanced understanding of gait impairment beyond traditional walking speed measurements.
• The study facilitates the integration of advanced gait analysis techniques into clinical research and practice for MS and potentially other disabilities.