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Analysis of human ambulation as a chaotic time-series: with nonlinear dynamics tools
Mouaz Al Kouzbary1, Hamza Al Kouzbary1, Jingjing Liu1
1Center for Applied Biomechanics, Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia.
Computer Methods in Biomechanics and Biomedical Engineering
|September 4, 2024
Summary
Human gait complexity increases with speed, impacting robotic prostheses control. Stability analysis using fractal dimension and spectral entropy reveals insights into locomotion dynamics for advanced prosthetic design.
Area of Science:
- Biomechanics and Robotics
- Human Locomotion Analysis
- Control Systems Engineering
Background:
- Understanding human ambulation complexity is crucial for developing advanced robotic prostheses.
- Previous research has explored gait stability, but comprehensive analysis integrating complexity metrics is needed.
- Investigating the relationship between gait parameters and control system requirements is essential for functional prosthetic design.
Purpose of the Study:
- To investigate the complexity and stability of human ambulation across different conditions.
- To explore the implications of these gait characteristics on robotic prostheses control systems.
- To analyze gait dynamics during running and stair ambulation using advanced computational methods.
Main Methods:
- Collected motion data from 14 healthy individuals using seven inertial measurement units.
- Participants performed running at varying speeds and stair ascent/descent tasks.
- Analyzed data for fractal dimension, spectral entropy, and Lyapunov exponent (LyE) using multiple calculation approaches.
Main Results:
- Spectral entropy values were 0.538 for stairs and 0.575 for running, indicating increased complexity with speed.
- Lyapunov exponent analysis revealed minimal variation in tibia orientation during stair ascent/descent.
- Two-way ANOVA confirmed significant effects of ambulation speed and type on spectral entropy; fractal dimension varied significantly with speed.
Conclusions:
- Human ambulation exhibits increased complexity and uncertainty with higher speeds, a key factor for prosthetic control.
- Stair ambulation demonstrates a degree of stability in tibia orientation, relevant for prosthetic design.
- Findings provide critical data for enhancing the adaptability and performance of robotic prostheses control systems.
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