Establishing reference criteria for diagnosing normal gait patterns similarity using dynamic time warping.

Area of Science:

• Biomechanics
• Kinetics and Kinematics
• Gait Analysis

Background:

• Gait pattern analysis is crucial for rehabilitation.
• Dynamic Time Warping (DTW) offers a method for quantifying gait similarity.
• Establishing normative data is essential for clinical application.

Purpose of the Study:

• To establish reference criteria for evaluating gait pattern similarity during normal gait.
• To utilize dynamic time warping (DTW) for quantitative gait analysis.
• To provide benchmarks for assessing gait in research and clinical settings.

Main Methods:

• Implemented the dynamic time warping (DTW) algorithm using the R programming language.
• Conducted DTW analyses on 3D motion analysis data from 55 healthy participants' ankle, knee, and hip joints.
• Categorized DTW analyses into within-subject same limb, between-subjects same limb, and within-subject opposite limb comparisons.

Main Results:

• Provided reference criteria for gait pattern similarity as estimated marginal means and 95% confidence intervals.
• Identified statistically significant differences in gait patterns across the analyzed groups.
• Demonstrated variations in gait similarity based on within-subject same limb, between-subjects same limb, and within-subject opposite limb comparisons.

Conclusions:

• The study underscores the necessity of evaluating patient gait similarity against both healthy norms and their own contralateral limb.
• Findings support the precise assessment of gait patterns for effective rehabilitation strategies.
• Reference criteria established by this study can enhance the clinical utility of gait analysis research.