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Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait
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Zhang, Jie, Zhang, Kai, Feng, Jianfeng and Small, Michael (2010) Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait. PL o S Computational Biology, Vol.6 (No.12). doi:10.1371/journal.pcbi.1001033 ISSN 1553-734X.
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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1001033
Abstract
Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics Q Science > QP Physiology |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing Faculty of Science, Engineering and Medicine > Science > Computer Science |
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Library of Congress Subject Headings (LCSH): | Gait in humans, Neuromuscular diseases -- Diagnosis, Pattern perception, Dimension reduction (Statistics) | ||||
Journal or Publication Title: | PL o S Computational Biology | ||||
Publisher: | Public Library of Science | ||||
ISSN: | 1553-734X | ||||
Official Date: | 16 December 2010 | ||||
Dates: |
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Volume: | Vol.6 | ||||
Number: | No.12 | ||||
DOI: | 10.1371/journal.pcbi.1001033 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Funder: | Hong Kong Polytechnic University (HKPU), Fu dan da xue (Shanghai, China) [Fudan University] | ||||
Grant number: | G-YX0N (Hong Kong) |
Data sourced from Thomson Reuters' Web of Knowledge
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