Comparing Gait Trials with Greedy Template Matching

Area of Science:

• Biomechanics
• Wearable Technology
• Data Analysis

Background:

• Gait assessment is crucial for monitoring neurological diseases and elderly populations.
• Standard gait features are often insufficient for detailed trial comparison.
• Inertial Measurement Units (IMUs) offer potential for longitudinal gait analysis.

Purpose of the Study:

• To introduce a novel algorithm for comparing two gait trials using IMU data.
• To develop a quantitative measure of gait similarity between trials.

Main Methods:

• The algorithm extracts step templates from one gait trial.
• It employs a greedy template matching approach to find similar steps in a second trial.
• A similarity index (SId) between 0 and 1 is generated.

Main Results:

• The algorithm successfully quantifies gait similarity.
• Results demonstrated effectiveness in both healthy subjects and those with multiple sclerosis.
• The SId reflects the similarity of gait patterns observed in the trials.

Conclusions:

• The developed algorithm provides a robust method for comparing gait trials.
• This tool is valuable for both inter-individual gait comparisons and longitudinal patient follow-up.
• The approach enhances the utility of IMUs in clinical gait analysis.