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Published on: April 13, 2016
Understanding the complexity of human gait dynamics
Nicola Scafetta1, Damiano Marchi, Bruce J West
1Department of Physics, Duke University, Durham, North Carolina 27708, USA.
Chaos (Woodbury, N.Y.)
|July 2, 2009
Summary
Human gait stride intervals show fractal patterns. These patterns change with walking speed, age, and neurodegenerative diseases, indicating system stress and evolution.
Area of Science:
- Dynamical systems analysis
- Human biomechanics
- Neuroscience
Background:
- Human gait exhibits complex temporal dynamics.
- Fractal and multifractal properties are observed in stride interval time series.
- These properties may reflect system state under varying conditions.
Purpose of the Study:
- To investigate fractal scaling in human gait stride intervals.
- To analyze how fractal properties change with stress (walking pace) and system evolution (age, disease).
- To present a model simulating these dynamical network properties.
Main Methods:
- Analysis of time series data of human gait stride intervals.
- Examination of records from subjects across different ages and health statuses.
- Utilizing fractal and multifractal scaling analysis.
- Development of a supercentral pattern generator model.
Main Results:
- Fractal and multifractal properties were confirmed in human gait stride intervals.
- Scaling properties varied significantly with walking pace (stress).
- Changes in fractal scaling were observed with aging and neurodegenerative diseases (system evolution).
Conclusions:
- Human gait dynamics exhibit fractal characteristics sensitive to stress and evolution.
- Fractal analysis provides insights into the physical maturation and degeneration of biological systems.
- The supercentral pattern generator model can simulate observed gait dynamics.
