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    Rhythmic dynamics and synchronization via dimensionality reduction: Application to human gait

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    Rhythmic dynamics and synchron ...
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    Genre
    Journal Article
    Date
    2010-01-01
    Author
    Zhang, J
    Zhang, K
    Feng, J
    Small, M
    Subject
    Ankle
    Biomechanical Phenomena
    Computational Biology
    Gait
    Humans
    Knee
    Models, Biological
    Walking
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/5551
    
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    DOI
    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 highdimensional 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 ankleknee 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.
    Citation to related work
    Public Library of Science (PLoS)
    Has part
    PLoS Computational Biology
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    ae974a485f413a2113503eed53cd6c53
    http://dx.doi.org/10.34944/dspace/5533
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