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Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics

Cited 20 time in Web of Science Cited 21 time in Scopus
Authors
Ahn, Jooeun; Hogan, Neville
Issue Date
2013-09
Publisher
PUBLIC LIBRARY SCIENCE
Citation
PLOS ONE, Vol.8 No.9, pp. 1-10
Keywords
Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics복합학
Abstract
Stride intervals of normal human walking exhibit long-range temporal correlations. Similar to the fractal-like behaviors observed in brain and heart activity, long-range correlations in walking have commonly been interpreted to result from chaotic dynamics and be a signature of health. Several mathematical models have reproduced this behavior by assuming a dominant role of neural central pattern generators (CPGs) and/or nonlinear biomechanics to evoke chaos. In this study, we show that a simple walking model without a CPG or biomechanics capable of chaos can reproduce long-range correlations. Stride intervals of the model revealed long-range correlations observed in human walking when the model had moderate orbital stability, which enabled the current stride to affect a future stride even after many steps. This provides a clear counterexample to the common hypothesis that a CPG and/or chaotic dynamics is required to explain the long-range correlations in healthy human walking. Instead, our results suggest that the long-range correlation may result from a combination of noise that is ubiquitous in biological systems and orbital stability that is essential in general rhythmic movements.
ISSN
1932-6203
Language
English
URI
https://hdl.handle.net/10371/116874
DOI
https://doi.org/10.1371/journal.pone.0073239
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College of Education (사범대학)Dept. of Physical Education (체육교육과)Journal Papers (저널논문_체육교육과)
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