The Automatization of the Gait Analysis by the Vicon Video System: A Pilot Study

Area of Science:

• Biomechanics
• Medical Diagnostics
• Data Science

Background:

• Accurate diagnosis of musculoskeletal disorders relies on precise gait analysis.
• Modern measuring instruments and automated methods can enhance diagnostic speed.
• Gait analysis is crucial for understanding human locomotion and identifying abnormalities.

Purpose of the Study:

• To automate the gait analysis method for faster and more accurate diagnosis.
• To develop a data clusterization approach for classifying different gait types.
• To investigate kinematic parameters for distinguishing between various walking patterns.

Main Methods:

• Utilized the Vicon Nexus system with 27 reflective markers for motion capture.
• Employed goniometry techniques to collect angular data during various gaits.
• Applied data interpolation and clustering algorithms to analyze gait patterns.
• Recorded multiple trials for casual and non-standard gaits (shuffling, lameness, etc.) in six healthy subjects.

Main Results:

• Successfully clustered gait data into four distinct groups based on interpolated angle data.
• Identified statistically significant differences between the derived cluster groups.
• Presented typical angulograms and calculated average angles for each cluster.
• Demonstrated the effectiveness of the proposed data clusterization approach.

Conclusions:

• The automated gait analysis method effectively differentiates between various walking patterns.
• The developed clusterization technique provides a quantitative basis for gait classification.
• This approach holds potential for improving the diagnosis of musculoskeletal conditions through objective gait assessment.