Comparison of sensitivity coefficients for joint angle trajectory between normal and pathological gait

Area of Science:

• Biomechanics and Biomedical Engineering
• Human Movement Analysis

Background:

• Gait recordings are subject to significant variability, complicating clinical analysis and treatment assessment.
• Accurate comparison of gait data is crucial for medical diagnosis and evaluating therapeutic interventions.

Purpose of the Study:

• To assess group homogeneity by analyzing dispersion around a reference gait curve.
• To compare normal and pathological gait waveforms using joint angle trajectories.
• To evaluate the effectiveness of different data analysis techniques for gait comparison.

Main Methods:

• Utilized the APAS system for tracking gait data.
• Developed a lower limb model to compute joint angle trajectories for five distinct groups: healthy males, healthy females, children, individuals with drop foot, and individuals with Trendelenburg's sign.
• Employed waveform parameterizations, Root Mean Square (RMS), Integrated Absolute Error (IAE), and correlation coefficients for comparative analysis.

Main Results:

• Quantitative scores were derived, indicating the similarity in shape between different gait curves.
• The study demonstrated the ability to differentiate between normal and pathological gait patterns based on joint angle analysis.
• Multiple data analysis techniques provided complementary information, enhancing the accuracy of gait assessment.

Conclusions:

• Comparative analysis of joint angle curves is effective for characterizing gait patterns.
• The chosen analytical methods provide valuable insights into the degree of similarity between gait waveforms.
• Employing a combination of data analysis techniques yields more precise and reliable information for gait studies.