Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics
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 mathe...
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2014
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| Online Access: | http://hdl.handle.net/1721.1/83473 https://orcid.org/0000-0001-5366-2145 |
| _version_ | 1826205308852109312 |
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| author | Ahn, Jooeun Hogan, Neville |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Ahn, Jooeun Hogan, Neville |
| author_sort | Ahn, Jooeun |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:10:39Z |
| format | Article |
| id | mit-1721.1/83473 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:10:39Z |
| publishDate | 2014 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/834732022-10-01T13:32:42Z Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics Ahn, Jooeun Hogan, Neville Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Massachusetts Institute of Technology. Department of Mechanical Engineering Ahn, Jooeun Hogan, Neville 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. United States. Defense Advanced Research Projects Agency (Warrior Web program BAA-11-72) Eric P. and Evelyn E. Newman Fund Gloria Blake Fund 2014-01-06T14:08:38Z 2014-01-06T14:08:38Z 2013-09 2013-03 Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/83473 Ahn, Jooeun, and Neville Hogan. “Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics.” Edited by Ramesh Balasubramaniam. PLoS ONE 8, no. 9 (September 23, 2013): e73239. https://orcid.org/0000-0001-5366-2145 en_US http://dx.doi.org/10.1371/journal.pone.0073239 PLoS ONE http://creativecommons.org/licenses/by/2.5/ application/pdf Public Library of Science PLoS |
| spellingShingle | Ahn, Jooeun Hogan, Neville Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics |
| title | Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics |
| title_full | Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics |
| title_fullStr | Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics |
| title_full_unstemmed | Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics |
| title_short | Long-Range Correlations in Stride Intervals May Emerge from Non-Chaotic Walking Dynamics |
| title_sort | long range correlations in stride intervals may emerge from non chaotic walking dynamics |
| url | http://hdl.handle.net/1721.1/83473 https://orcid.org/0000-0001-5366-2145 |
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